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arXiv cs.CL
arXiv cs.CL
7/15/2026
CANDI: Contextual Alignment for Niche Domains Question Answering

CANDI: Contextual Alignment for Niche Domains Question Answering

Short summary

A new benchmark dataset called CANDI-QA evaluates LLMs on delivering accurate, context-sensitive answers in specialized domains like medical diagnostics and financial advisory. It includes expert-curated QA pairs split into factual extraction tasks and multi-hop reasoning tasks requiring situational inference. Evaluation of over ten LLMs alongside a proposed neuro-symbolic baseline (MTSS-Net) reveals significant limitations of current models in achieving contextual alignment for high-stakes applications.

  • •CANDI-QA benchmark tests LLMs in medical and financial niche domains
  • •Includes factual extraction and multi-hop applied inference question types
  • •Current LLMs show significant limitations without symbolic or contextual integration

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Read full article at arXiv cs.CL

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The original title is a survey title, not a news headline. I need to rewrite it as a news headline for a mobile feed.
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